Seismic data acquisition and processing techniques are used to generate a profile (image) of a geophysical structure (an horizon) of the strata underlying the land surface or seafloor (the earth subsurface). Among other things, seismic data acquisition involves the generation of acoustic waves and the collection of reflected/refracted versions of those acoustic waves to generate the image. This image does not necessarily provide an accurate location for oil and gas reservoirs, but it may suggest, to those trained in the field, the presence or absence of oil and/or gas reservoirs. Thus, providing an improved image of the subsurface in a shorter period of time is an ongoing process in the field of seismic surveying.
A somewhat more recent development in seismic acquisition is the use of so-called four-dimensional (4D) seismic surveying. 4D seismic surveying refers to the technique of taking one seismic survey of a particular geographical area at a first time (i.e., the baseline survey) and another seismic survey of the same geographical area at a later time (i.e., the monitor survey). The baseline survey and the monitor survey can then be compared for various purposes, e.g., to observe changes in the hydrocarbon deposits in a geographical area which has an active well operating therein. Different seismic surveys performed at different times for the same geographical area are also sometimes referred to as different “vintages”. In order for the comparison to be meaningful it is, therefore, important that the surveys be performed in a manner which is highly repeatable, i.e., such that the monitor survey is performed in much the same way (e.g., position of sources and receivers relative to the geography) as the baseline survey was performed.
Among other techniques used in 4D seismic data processing, is a technique known as 4D binning. 4D binning is a selection process in which the best matching subsets of traces within the full datasets acquired are identified. As will be appreciated by those skilled in the seismic arts, each “trace” refers to the seismic data recorded for one channel, i.e., between a source and a receiver. Currently performed as an early step in 4D seismic data processing, only the best matching subsets identified during the 4D binning process are considered for further seismic 4D comparison processes.
Conventional four-dimensional (4D) binning is performed in common mid-points, i.e., for each offset class and each mid-point bin, and only one, best-fitting coupled trace is kept for further 4D processing sequences. As will be appreciated by those skilled in the seismic arts, an “offset” refers to a distance relative to template of source and receiver lines used to perform the seismic acquisition. Offsets can be defined in various types or classes. For example, near offsets, mid offsets and far offsets are different classes of offsets which represent different (and increasing) distances from a shot point relative to the acquisition template. Additionally, a “mid-point bin” refers to a square or rectangular area which contains all of the midpoints that correspond to the same common midpoint. Fitting associated with selecting the best-fitting pair is calculated from various criteria, e.g., minimal source and receiver positioning misfit and minimal time-window normalized root mean square (NRMS) error between seismic traces. As will be appreciated by those skilled in the art, an NRMS error criterion refers to the RMS value of the difference between two input traces, normalized by the RMS values of the two input traces.
When performing 4D seismic data processing, it is desirable to select geological horizons in the vicinity of expected 4D changes, i.e., differences between the monitor survey and the baseline survey which are expected due to, e.g., the extraction of hydrocarbons. Selected target horizons, such as a reservoir horizon, are generally buried under laterally heterogeneous overburden and may carry proper dips. As will be appreciated by those skilled in the art, “dips” in this context refer to subsurface reflecting layers which have interfaces which are not perfectly horizontal. Then, with such media features, the midpoint is no longer the reflection point. Consequently, conventional 4D binning could select a couple of traces containing useless diffraction on target traces and discard the specular traces (obeying Snell-Descartes law of reflection) that carry the most important reflective information.
Accordingly, it would be desirable to provide systems and methods that avoid the afore-described problems and drawbacks associated with the improvement of seismic images based on preserving specular reflections on a depth target from 4D binning process.